Determination device

Abstract

To provide a determination device and the like capable of properly determining whether an object person is leaving a bed apparatus.SOLUTION: A determination device comprises: an acquisition unit which acquires vibration data respectively from a first sensor and a second sensor installed at a bed apparatus; and a control unit. The control unit determines that an object person is leaving the bed apparatus when acquiring vibration data in which the vibration data acquired from the first sensor and the vibration data acquired from the second sensor are generally equal to each other.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a determination device and the like. [Background technology]

[0002] Conventionally, there are known inventions for determining whether a subject on a bed apparatus has left the bed. For example, as described in Patent Document 1, there is known an invention for determining whether a user is on the bed apparatus or has left the bed apparatus based on vibrations detected by a vibration detection means. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2010-264193 A Summary of the Invention [Problem to be solved by the invention]

[0004] The present invention provides a determination device etc. that can appropriately determine whether a subject has left a bed apparatus. [Means for solving the problem]

[0005] In order to solve the above-mentioned problems, the determination device of this embodiment includes an acquisition unit that acquires vibration data from a first sensor and a second sensor installed on the bed device, and a control unit, and the control unit determines that the subject has left the bed when the vibration data acquired from the first sensor and the vibration data acquired from the second sensor are substantially identical to each other.

[0006] The program of this embodiment enables a computer capable of acquiring vibration data from a first sensor and a second sensor installed in the bed device to realize the function of determining that the subject has left the bed when the vibration data acquired from the first sensor is substantially identical to the vibration data acquired from the second sensor. Effect of the Invention

[0007] According to the present invention, it is possible to appropriately determine whether a subject has left the bed apparatus. [Brief description of the drawings]

[0008] [Figure 1] FIG. 2 is a diagram for explaining the whole of the present embodiment. [Diagram 2] FIG. 2 is a diagram for explaining a configuration according to the present embodiment. [Diagram 3] FIG. 1 is a diagram for explaining an overview of a detection device according to an embodiment of the present invention. [Figure 4] FIG. 11 is an operational flow diagram for explaining an erroneous determination process in the present embodiment. [Diagram 5] FIG. 4 is an operational flow diagram for explaining a first process in the present embodiment. [Figure 6] FIG. 11 is a diagram for explaining an operation example in the present embodiment. [Figure 7] FIG. 11 is a diagram for explaining an operation example in the present embodiment. [Figure 8] FIG. 11 is a diagram for explaining an operation example in the present embodiment. [Figure 9] FIG. 4 is a diagram for explaining an example of a setting table in the present embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] For example, as described in JP 2010-264193 A, a determination device is known that determines whether a subject is present on a bed apparatus or has left the bed. The determination device detects vibrations from a sensor device provided on the bed apparatus or a sensor device placed on a mattress on the bed apparatus. In general, the detection of vibrations from a sensor device means that the subject is present on the bed apparatus. Therefore, the determination device determines that the subject is present in bed when a certain level of vibration is detected from the sensor device, and that the subject has left the bed when no vibration is detected from the sensor device.

[0010] However, the sensor device can detect even minute changes in the subject. This is because the signal detected by the sensor device can detect the subject's bodily movements, and can detect even slight changes. As a result, for example, the sensor device can function as a bioinformation acquisition device to acquire the subject's bioinformation (heart rate, breathing, sleep state) from the vibrations (body movements) detected by the sensor device.

[0011] In this case, the sensor device detects even minute changes, so there is a problem in that it detects vibrations due to changes in air pressure, for example. For example, the sensor device may detect vibrations due to changes in air pressure caused by weather (for example, changes in air pressure caused by strong winds such as a typhoon) or due to changes in air pressure caused by opening or closing a door or window in a room.

[0012] Therefore, even if the subject is out of bed and there is no one on the bed apparatus, the sensor device detects vibrations (for example, detects a change in voltage value) in conjunction with a change in air pressure, which is a problem. If the sensor device erroneously detects vibrations, the determination device erroneously determines that the subject is in bed, even though there is no one on the bed apparatus (out of bed state).

[0013] In view of such problems, one embodiment of a determination device capable of appropriately determining the state of being in bed / out of bed as the state of a subject will be described below with reference to the drawings. Note that the following embodiment is an example of the application of the determination device of the present invention, and the scope of application of the present invention is not limited to the following embodiment.

[0014] [1. Entire system] Fig. 1 is a diagram for explaining an overall overview of a system 1 to which a determination device is applied. As shown in Fig. 1, the system 1 is configured to include a detection device 3 placed between the floor part of a bed device 10 and a mattress 20, and a processing device 5 for processing values ​​output from the detection device 3. The detection device 3 and the processing device 5 configure a determination device (determination system) that determines the state of a subject.

[0015] When a subject (hereinafter, referred to as "subject P" as an example) is present on the mattress 20, the detection device 3 detects the subject P's body vibrations (vibrations emitted from the human body). Then, the processing device 5 can acquire the state of the subject P based on the vibrations detected by the detection device 3. Although details will be described later, the processing device 5 can acquire, for example, the following states as the state of the subject P.

[0016] Whether the subject is on the bed apparatus 10 (mattress 20) or has left the bed apparatus 10 (mattress 20). - Heart rate, respiration, and activity level as biological information of the subject Subject movement (body movement) - Subject's posture. For example, side-lying, supine, sitting on edge, sitting upright, etc. The subject's position, e.g., whether they are in the center of the bed apparatus 10 or off to one side

[0017] In this embodiment, the calculated bioinformation value (e.g., respiratory rate, heart rate, activity level) can be output and displayed as the bioinformation value of the subject P. Note that, for example, a storage unit, a display unit, and the like may be provided in the detection device 3 to form an integrated device. In addition, the processing device 5 may be a general-purpose device, and is not limited to an information processing device such as a computer, and may be configured as a device such as a tablet or a smartphone.

[0018] The subject may be a person undergoing medical treatment or in need of nursing care, or may be a healthy person not in need of nursing care, an elderly person, a child, a person with a disability, or even a non-human animal.

[0019] Here, the detection device 3 is formed in a sheet shape so as to have a small thickness. As a result, even if the detection device 3 is placed between the bed device 10 and the mattress 20, it can be used without making the subject P feel uncomfortable, and therefore, the biological information value in bed can be measured for a long period of time.

[0020] The detection device 3 may be capable of detecting the vibration of the subject P. For example, an actuator with a strain gauge or a load cell that measures the load placed on the legs of the bed may be used. Also, by using a built-in acceleration sensor, the detection device 3 may be realized by, for example, a smartphone or tablet placed on the bed device 10.

[0021] In FIG. 1, the head side of the bed apparatus 10 (mattress 20) is direction H, the foot side is direction F, and when the subject P is in a supine position, the left side is direction L and the right side is direction R.

[0022] [2. Configuration] Next, the configuration of the system 1 will be described with reference to Fig. 2 to Fig. 4. The system 1 in this embodiment includes a detection device 3 and a processing device 5, and each functional unit (processing) may be realized by either one. In this embodiment, the processing device 5 functions as a determination device.

[0023] The processing device 5 includes a control unit 100, a signal acquisition unit 120, a storage unit 150, an input unit 160, and an output unit 170.

[0024] The control unit 100 controls the operation of the processing device 5 and is configured with one or more control devices. For example, it may be a control device such as a CPU (Central Processing Unit) or may be a SoC (System on a Chip) having multiple functions.

[0025] Moreover, the control unit 100 realizes various processes by reading and executing various programs stored in the storage unit 150. The control unit 100 may function as a bed exit determination unit 102, an erroneous determination processing unit 104, a biological information calculation unit 106, and a subject state determination unit 108 by executing the programs. In this embodiment, the control unit 100 operates as a whole, but it may also be provided in each of the detection device 3 and the processing device 5 as shown in FIG. 3 described later.

[0026] The bed leaving determination unit 102 determines whether the subject is on the bed apparatus 10 (in bed) or not on the bed apparatus 10 (out of bed). Here, the subject being in bed means that the subject is present on the bed apparatus 10 (mattress 20). The subject may be in a lying position or a sitting position, for example. Furthermore, the subject being out of bed means that the subject is not present on the bed apparatus 10 (mattress 20). In other words, it means a state in which no person is on the bed apparatus 10 (mattress 20). Furthermore, if a biological signal of the subject (for example, heart rate, breathing, etc.) is detected, it may be determined that the subject is present in bed, and otherwise it may be determined that the subject is out of bed.

[0027] For example, the bed exit determination unit 102 may determine that the subject has exited the bed when no vibration or load is detected from the vibration data received by the signal acquisition unit 120. The bed exit determination unit 102 may also determine that the subject has exited the bed when it cannot be determined that the subject is in bed.

[0028] The erroneous judgment processing unit 104 judges whether the subject has left the bed separately from the judgment result of the bed leaving judgment unit 102. That is, if the bed leaving judgment unit 102 judges that the subject is in bed even though the subject is not actually in bed, it is an erroneous judgment, and the erroneous judgment processing unit 104 judges that the subject has left the bed. The details of the processing of the erroneous judgment processing unit 104 will be described later.

[0029] The bioinformation calculation unit 106 calculates bioinformation based on the signal acquired from the signal acquisition unit 120. For example, the heartbeat (heart rate) and respiration (respiratory rate) are calculated as the bioinformation of the subject. For example, a method for calculating the bioinformation may be any of the known methods such as the method described in JP2017-047211A (Title of the invention: Bioinformation output device, bioinformation output method and program, Publication date: March 9, 2017).

[0030] The subject state determination unit 108 can determine the state of the subject. For example, the state of the subject can be determined as to whether the subject is asleep or awake. The sleep state of the subject may be determined from vibration data acquired by the signal acquisition unit 120, or may be determined based on the biological information output from the biological information calculation unit 106. For example, the subject state determination unit 108 may determine whether the subject is asleep or awake from the transition of the subject's heart rate and the transition of the respiratory rate. The method of determining the sleep state of the subject can be, for example, the method disclosed in JP 2015-12948 A (Name of invention: Sleep evaluation device, sleep evaluation method, and sleep evaluation program, Publication date: January 22, 2015), JP 2017-213421 A (Name of invention: Sleep evaluation device and program, Publication date: December 7, 2017), etc. In addition, any other known method of determining the sleep state of the subject may be used.

[0031] The subject state determination unit 108 may also determine the posture of the subject. For example, the subject state determination unit 108 may determine whether the subject is in a supine position or a lateral position. The subject state determination unit 108 may also determine whether the subject is sitting on the edge of the bed or sitting on the side. The subject state determination unit 108 may determine the posture based on vibration data acquired by the signal acquisition unit 120, or may determine the posture based on a change in load. As a method for determining the posture of the subject, for example, a method disclosed in JP 2019-98069 A (Name of invention: Posture determination device, Publication date: June 24, 2019) or the like may be used. In addition, any other known method for determining the posture of the subject may be used.

[0032] The signal acquiring unit 120 acquires a signal output by the detection device 3. Here, the detection device 3 outputs, for example, vibration data indicating vibration. In this embodiment, the detection device 3 outputs time-series data of vibration. For example, if the detection device 3 is configured with a piezoelectric sensor, it converts the detected pressure into a voltage value and outputs data so that the change in time series can be understood. Furthermore, the time-series data output by the detection device 3 may be a value that indicates the change in time series (a value that is output continuously), or may be waveform data indicating the time series.

[0033] Furthermore, when the vibration data is too large, the detection device 3 may attenuate the vibration data before outputting it. The detection device 3 may output the vibration data as an analog signal, may convert the vibration data into a digital signal, or may output a quantified version. In this embodiment, the detection device 3 outputs an analog signal based on the vibration.

[0034] The signal acquisition unit 120 outputs the input vibration data to the control unit 100. The control unit 100 converts the analog vibration data into a digital voltage signal at a predetermined sampling interval. If the signal magnitude is too large, the signal is attenuated and converted into a digital signal. After converting into a digital signal, the control unit 100 digitizes the signal and stores it in the acquired data storage area 154 as acquired data. That is, the vibration data acquired by the signal acquisition unit 120 is sampled, quantized, and coded by the control unit 100 and stored in the acquired data storage area 154 as acquired data.

[0035] The storage unit 150 stores various data and programs for the operation of the processing device 5. The control unit 100 realizes various functions by reading and executing the programs stored in the storage unit 150. Here, the storage unit 150 is configured with a semiconductor memory (e.g., an SSD (Solid State Drive) or an SD card (registered trademark)), a magnetic disk device (e.g., an HDD (Hard Disk Drive)), or the like. The storage unit 150 may be a built-in storage device or a removable external storage device. It may also be a storage area of ​​an external server such as a cloud.

[0036] The storage unit 150 reserves areas for a subject data storage area 152 and an acquired data storage area 154 , and stores a parameter table 156 .

[0037] The subject data storage area 152 stores subject data. The subject data is data related to the subject, and each data is stored in chronological order. The subject data that can be stored include, for example, the result of in-bed / out-of-bed determined by the bed exit determination unit 102, the biological information calculated by the biological information calculation unit 106, the subject's state determined by the subject state determination unit 108, and the like. These data (information) can be stored in chronological order for each subject.

[0038] The acquired data storage area 154 stores the acquired data output by the control unit 100. The acquired data stores information (raw data) based on the vibration data acquired by each sensor. The acquired data can also store related information other than the vibration data.

[0039] The parameter table 156 stores parameters such as a judgment value (judgment threshold) and a judgment time used by the control unit 100 (for example, the erroneous judgment processing unit 104) to judge whether the subject has left the bed. The parameters may be changed by the user or may be stored in advance. For example, in the case of vibration data quantized to 12 bits, the parameters may be calculated from atmospheric pressure change data of past typhoons, etc., and the judgment value may be set to 24 or less as an initial value and the judgment time to 10 seconds as a default value, and the parameters may be changed to fit the environment.

[0040] The input unit 160 receives operational input from a user. For example, the user may perform various operational inputs, such as an operation to start acquiring the user's state or adjusting the sensitivity of the detection device 3.

[0041] The output unit 170 outputs various information. For example, it is configured with a display device such as a liquid crystal display, a light emitting member such as an LED, a speaker that outputs sound or voice, an interface that outputs data to another recording medium, etc. Also, the input unit 160 and the output unit 170 may be configured as a touch panel by being integrated together.

[0042] Moreover, the output unit 170 can not only output various information, but also display, for example, a report based on the state of the subject or the state. For example, the output unit 170 can output a sleep diary based on the sleeping state and biological information of the subject. The sleep diary can output, for example, the sleeping / wakefulness state of the subject for one day, and also the state of being in bed / out of bed of the subject. As a method for outputting the sleep diary, for example, a method disclosed in JP 2016-144627 A (Name of invention: Biological information output device, biological information output method and program, Publication date: August 12, 2016) or the like can be used. As a method for outputting the sleep diary, any known method can be used.

[0043] 2 conceptually explains the configuration when the processing device 5 functions as a determination device. These configurations may be realized, for example, by a single device capable of detecting vibration, or may be configured separately as the detection device 3 and the processing device 5 as shown in Fig. 1. Also, instead of the processing device 5, it may be realized by an external server capable of providing the same service.

[0044] The detection device 3 has a sensor that detects vibrations, or is configured to be connectable to an external sensor. The detection device 3 transmits a signal (vibration data) related to the vibrations detected by the sensor to the processing device 5 via a communication unit. The timing of transmitting the vibration data from the detection device 3 to the processing device 5 and the timing of the processing device 5 storing the vibration data may be in real time or at predetermined time intervals.

[0045] Here, an overview of the detection device 3 will be described with reference to Fig. 3. Fig. 3 is a view of the bed apparatus 10 (mattress 20) as viewed from above. In Fig. 3, the upper side corresponds to direction H in Fig. 1, and the lower side corresponds to direction F in Fig. 1. The right side of Fig. 3 corresponds to direction F in Fig. 1, and the left side of Fig. 4 corresponds to direction R in Fig. 1.

[0046] The detection device 3 is placed between the bed apparatus 10 and the mattress 20 or on the mattress 20. The place where it is placed is preferably near the back of the patient, and therefore at least in a direction closer to the H side than the center of the bed apparatus 10 (mattress 20).

[0047] The detection device 3 also has a built-in sensor. The sensor is, for example, a vibration sensor 320, and can detect the vibration (body vibration) of the subject. At least two sensors are provided, and in FIG. 3, for example, two sensors (vibration sensor 320a, vibration sensor 320b) are provided on the left and right sides of the detection device 3. The detection device 3 or the processing device 5 can acquire bioinformation values ​​(e.g., heart rate, respiratory rate) based on bioinformation (e.g., heart rate, respiration, etc.) based on the detected small vibration of the subject. The detection device 3 or the processing device 5 can also acquire the movement (body movement) of the subject based on the detected large vibration of the subject. Here, the movement of the subject refers to, for example, the movement of the subject changing his / her posture by turning over in bed, or the movement of the subject's limbs.

[0048] The vibration sensor 320a and the vibration sensor 320b are provided at a predetermined distance from each other. The distance between the two sensors may be, for example, approximately the width of the patient in the lateral direction, and is preferably about 15 to 60 cm.

[0049] The detection device 3 and the processing device 5 can be connected by wire or wirelessly. The detection device 3 may store vibration data in an external recording medium (e.g., an SD card). The processing device 5 may read and acquire the vibration data from the recording medium.

[0050] [3. Processing flow] [3.1 False positive processing] Next, the erroneous judgment process in this embodiment will be described with reference to Fig. 5 and Fig. 6. In the erroneous judgment process, after the bed exit judgment unit 102 judges whether the patient is in bed or not, it judges whether the judgment is appropriate. If the judgment of the bed exit judgment unit 102 is not appropriate, the erroneous judgment processing unit 104 executes a process to make the judgment appropriate.

[0051] First, the control unit 100 initializes the value of the timer t and the cumulative value absDSum to "0" (step S100). Here, the timer t is a variable indicating time, and may be a simple timer. The cumulative value absDSum will be described later.

[0052] The control unit 100 reads four variables (step S102). The variables read here are the following four:

[0053] Vibration data raw0: Vibration data detected by the first sensor Vibration data raw1; vibration data detected by the second sensor gain: Flag indicating whether damping processing has been performed on the vibration data mentioned above · state: state of the subject. The state of the subject that has already been determined

[0054] Here, the vibration data may be, for example, data based on raw data (raw waveform data) output from the detection device 3. Furthermore, the vibration data may be output in, for example, a CSV format or a unique data format.

[0055] The vibration data may be data obtained by sampling at a predetermined interval the values ​​output from the detection device 3 (sensor). For example, the control unit 100 may perform sampling at 12 bits and 128 Hz as a first format, or may perform sampling at 10 bits and 16 Hz as a second format.

[0056] Furthermore, the control unit 100 may convert (downsample) the vibration data acquired from the above-mentioned detection device 3 into data with an even lower sampling frequency. For example, vibration data of 128 Hz may be converted into data of 16 Hz and output.

[0057] The control unit 100 may also apply a low-pass filter (LPF) to the output data. For example, the control unit 100 may process the signal using an LPF with a cutoff frequency of 5 Hz, a tap count of 1 s, and a window function of a Hamming window.

[0058] Moreover, gain is a flag indicating whether or not attenuation processing has been applied to the vibration data. It becomes "1" when the control unit 100 applies attenuation processing when encoding based on the signal received from the detection device 3, or when the detection device 3 applies attenuation processing to the signal when it receives the signal from the sensor. In other words, when gain is "0", it indicates that attenuation processing has not been applied to the vibration data.

[0059] Moreover, state is the judgment of in bed / out bed judged by the out-of-bed judgment unit 102, and is a flag for whether to perform erroneous judgment processing. In other words, when state is "0", the control unit 100 has already judged the subject to be "out of bed". Therefore, there is no need to execute erroneous judgment processing.

[0060] Also, when the state is "1", it indicates that the subject has been determined to be "in bed" by any method. For example, when the state is "1", it may indicate that the subject is "asleep" or "awake". When the state is "1", it may indicate that the subject is present on the bed apparatus 10 (mattress 20).

[0061] It should be noted that the system may be used to execute erroneous judgment processing even when this state is "0." For example, in comparison with the above description, it is necessary to execute erroneous judgment processing all the time, but by executing erroneous judgment processing from when "out of bed" is judged, it is possible to judge whether the judgment of out of bed or in bed is always an erroneous judgment, and it is possible to shorten the time during which the judgment of "in bed" is erroneously judged.

[0062] The control unit 100 executes a judgment process based on the above parameters. First, the control unit 100 judges whether the currently acquired vibration data is already attenuated data (step S104). That is, the control unit 100 judges whether the vibration data raw0 and the vibration data raw1 have each been subjected to attenuation processing. Here, if either the vibration data raw0 or the vibration data raw1 has been subjected to attenuation processing (step S104; No), the control unit 100 initializes the variables of the timer t and the accumulated value absDsum ("0"), and proceeds to step S114.

[0063] In this embodiment, when the subject is not in bed, the detected data of the vibration data raw0 and the vibration data raw1 is small, so that the attenuation process is not executed in the first place. Therefore, when the vibration data raw0 and the vibration data raw1 are attenuated, the process proceeds to step S112 (step S104; No→step S112).

[0064] In the present embodiment, the case where the attenuation process is performed when the signal detected as the vibration data is large is described as an example. For example, if the attenuation process is not performed on the vibration data in the first place, the process of step S104 does not need to be performed.

[0065] In step S104, when it is determined that the vibration data is not attenuated data, the control unit 100 determines whether the subject is in bed (step S104; Yes → step S106). That is, the bed leaving determination unit 102 determines whether the subject is currently in bed or out of bed.

[0066] If the subject has already left the bed, the control unit 100 is not a target of this process, so that the control unit 100 initializes the parameters and checks whether to end the process (step S106; No→step S112).

[0067] Furthermore, if it is determined in step S106 that the subject is in bed, the control unit 100 determines whether or not body movement of the subject has been detected (step S108). Here, if the vibration data raw0 and raw1 exceed a certain range of values, it is assumed that body movement (body movement) of the subject has been detected. The certain range refers to the same range as the condition for applying attenuation processing to the data. Here, if body movement of the subject is detected (step S108; No), the control unit 100 initializes variables and checks whether to end processing.

[0068] Here, if there is no body movement, the control unit 100 executes a first process. The first process is a process for determining whether the state of the subject is "in bed" or "out of bed", and changing the state of the subject to "out of bed" if the state of the subject is newly determined to be "in bed".

[0069] Continuing with the explanation of Fig. 4, after the control unit 100 executes step S110 or step S112, the control unit 100 judges whether or not to end this process (step S114). Here, when the control unit 100 judges that this process has not yet ended, the control unit 100 returns to step S102 and reads the next data (step S114; No -> step S102). Also, the control unit 100 ends the execution of the error judgment process based on a predetermined condition or a predetermined operation (step S114; Yes).

[0070] [3.2 First process] The first process executed in step S110 in FIG. 4 will be described with reference to FIG.

[0071] First, the control unit 100 judges whether the variable flag is "0" or not (step S200). The variable flag indicates "0=no erroneous judgment due to erroneous judgment processing" or "1=erroneous judgment due to erroneous judgment processing".

[0072] When the variable flag is "0" (step S200; Yes), the control unit 100 judges whether the vibration data output from the two sensors are substantially the same. Note that the vibration data being substantially the same (substantially the same vibration data) indicates that the amplitude and phase of the vibration waveforms of the vibration data raw0 and the vibration data raw1 are similar. In other words, a state in which a plurality of vibration data are the same vibration data does not necessarily mean that the vibration data are completely the same, but also includes vibration data with slight differences.

[0073] First, the absolute values ​​of the vibration data output from the two sensors are accumulated (step S202). That is, the absolute value of the difference between the vibration data (raw0, raw1) output from the two sensors is added to the accumulated value absDsum (absDsum=absDsum+|raw0-raw1|).

[0074] Here, when the accumulated value absDsum becomes larger than the judgment value, the control unit 100 initializes each parameter (variable) (step S204; Yes->step S206). That is, the control unit 100 sets the timer t=0 and the accumulated value absDsum=0.

[0075] Moreover, when the cumulative value absDsum is equal to or smaller than the judgment value, the control unit 100 increments (increases by 1) the timer t (step S204; No→step S208).

[0076] Here, the determination value is a value that is determined in advance in accordance with the atmospheric pressure. For example, the determination value can be expressed by the following formula:

[0077] Judgment value = Sampling frequency (16Hz) × Judgment time T of maximum integration section × Judgment coefficient D Here, the sampling frequency is the frequency at which the vibration data is sampled. For example, in the process of FIG. 4, the data is converted to 16 Hz, so 16 Hz is applied. The judgment time T is the judgment time T at which the difference in the vibration data is accumulated and reaches the maximum integration interval. The judgment coefficient D is a value determined in advance in accordance with the air pressure. For example, it is appropriately set according to the environment in which the detection device 3 is installed.

[0078] For example, when the vibration data is quantized as 12-bit or 10-bit data, the values ​​in FIG. 7(c) may be used as the default values ​​of the parameters used in the misjudgment process. For example, when the vibration data is quantized as 12-bit data, the judgment coefficient D may be set to 24 and the judgment time T may be set to 10 seconds. In particular, since the judgment coefficient D varies depending on the usage environment and the sensor device used, it is desirable to adjust it according to the environment. In other words, by changing the judgment coefficient D, the control unit 100 can use a judgment value for each sensor device or a judgment value according to the environment.

[0079] For example, when installed in a patient's room, the value of the pressure change caused by the opening and closing of the door is measured, and the value of the judgment coefficient D is set so that it is judged that the patient is out of bed. In other words, the judgment value is set so that it is not judged that the patient is in bed.

[0080] Furthermore, when data is acquired in which a change in atmospheric pressure has occurred due to a typhoon or the like, a value that will not result in an erroneous determination is set as the determination coefficient D. This determines a determination value that will not result in an erroneous determination.

[0081] In addition, the control unit 100 may calculate the absolute value of the difference from multiple pieces of data in which the patient was previously determined to be in bed at a time when the patient should have been out of bed due to changes in air pressure, etc., and use the average value as the initial value of the judgment coefficient D, which may then be adjusted as appropriate to suit the environment and individual.

[0082] If the control unit 100 performs the judgment by a method other than the absolute value of the difference, for example, by the correlation coefficient, which is the third method described above, the judgment value may be set for an arbitrary correlation coefficient at a single judgment time T, or for the average value, maximum value, or minimum value of the correlation coefficient in the judgment section transitioned for every arbitrary number of data. For example, it may be judged as getting out of bed when the correlation coefficient calculated for the vibration data for 10 seconds up to the current time is 0.95 or more, or the correlation coefficient for the vibration data for 10 seconds may be calculated every second, and then the average value of the correlation coefficient for 10 seconds (10 pieces) from the start of the calculation may be set to 0.95 or more, or it may be judged as getting out of bed when the minimum or maximum value of the correlation coefficient is 0.95 or more.

[0083] Next, when the value of the timer t is equal to or greater than the judgment time T, the control unit 100 judges that the subject has left the bed (step 210; Yes → step S212). At this time, the bed leaving judgment unit 102 erroneously judges that the subject is in bed, but the erroneous judgment processing unit 104 judges that the subject has left the bed, thereby correcting the erroneous judgment.

[0084] Returning to step S200, the control unit 100 updates the cumulative value absDsum with the difference of the latest vibration data when the variable flag is not 0 (step S200; No -> step S214). That is, the cumulative value absDsum is calculated by the following formula. Here, the control unit 100 may end the erroneous determination process without updating absDsum at the point when t=T and flag=1 are reached and the bed exit determination is made.

[0085] Accumulated value absDsum = accumulated value absDsum - oldest |raw0-raw1| +Latest |raw0-raw1| As a result, the cumulative value absDsum is always the sum (cumulative value) of the differences in the vibration data going back a predetermined time from the present.

[0086] Here, if the accumulated value absDsum exceeds the judgment value, the variables are reset (step S216; Yes->step S218). That is, the control unit 100 sets the timer t=0, the accumulated value absDsum=0, and the variable flag=0.

[0087] In this way, by executing the first process, the control unit 100 can correct a state in which the subject is actually out of bed but has been changed to being in bed due to a change in air pressure.

[0088] In the above embodiment, the number of sensors is two, but more than two sensors may be provided. For example, when three or more sensors are provided, the control unit 100 may perform processing using two of the sensors. The control unit 100 may also integrate the results of processing using different combinations of sensors and determine whether or not the patient has left bed by the logical sum or logical product of the flags.

[0089] In the above-described embodiment, in order to determine whether each vibration data is substantially the same, the accumulated absolute value of the difference between the vibration data is used as the first method. Other methods may be used to determine whether each vibration data is substantially the same.

[0090] For example, as a second method, the control unit 100 may calculate the difference between the vibration data raw0 and the vibration data raw1, and determine that the two vibration data are substantially the same when a difference equal to or less than a predetermined threshold (for example, when the vibration data is quantized to 12 bits, the vibration data is equal to or less than the judgment value of 24) is continuously detected for a judgment time T (for example, 10 seconds) or more. In this case, the control unit 100 may compare the absolute value of the difference with a reference for each sampling, instead of accumulating the difference. In addition, the resolution of the quantization described above is not limited to this, and may be a different number of bits. In addition, the judgment value referred to by the control unit 100 may be adjusted taking into account the characteristics of the sensor used. According to the second method, when the difference between the vibration data is continuously detected for a period equal to or less than the judgment value, the bed apparatus determines that the subject has left the bed.

[0091] As a third method, the control unit 100 may calculate a correlation coefficient between the vibration data acquired from the first sensor and the vibration data acquired from the second sensor, and if the correlation coefficient is equal to or greater than a predetermined threshold (e.g., 0.95), determine that the two vibration data are substantially the same. In this case, the control unit 100 may determine whether the correlation coefficient has been equal to or greater than the predetermined threshold for a determination time T or more.

[0092] [4. Example of operation] Next, an actual operation example will be described. FIG. 6 shows the output values ​​of the variables. Vibration data raw0 and vibration data raw1 are shown on the left. Also, state is a value of getting out of bed / being in bed judgment. Here, when the getting out of bed judgment unit 102 judges getting out of bed, 0 is output, and when it judges being in bed, 1 is output. Also, state may indicate other states. For example, when the sleep state of the subject is acquired as sleeping or awake, "1" may be output, and when the sleep state cannot be acquired, "0" may be output. In this embodiment, as a result, data that is judged as getting out of bed from the beginning and is not subject to erroneous judgment processing is output as "0". Therefore, the control unit 100 does not subject data including D102 to erroneous judgment processing.

[0093] Furthermore, gain is a flag indicating whether or not attenuation processing has been performed. For example, when gain(raw0) is "0", attenuation processing has not been performed on the vibration data raw0 (the value is output as is). In addition, the difference |raw0-raw1| of the vibration data, the accumulated value absDsum, and the variable flag are respectively recorded. When the variable flag is "1", the control unit 100 determines that the subject has "left the bed" regardless of the result of the bed leaving determination unit 102.

[0094] Here, the section in which the subject's body movement is detected is not subject to judgment. For example, the area surrounded by D100 is output with vibration data that is much larger than normal (for example, exceeds 1000). In this case, it is determined that the subject's body movement is included in the vibration data, and it is not subject to erroneous judgment processing.

[0095] Referring to the data included in D104, the control unit 100 calculates the cumulative value absDsum from the fact that |raw0-raw1| in the row of t10 is output as "14". Then, when time T is reached in the row of t34, if the cumulative value absDsum is equal to or less than the judgment value, the flag is output as "1". That is, at t34, the control unit 100 determines that the patient is "in bed" because the state is "1", but corrects this to "out of bed" because the flag is "1".

[0096] When the row of t36 is judged, the difference value of time t10 is subtracted, and the difference value of t36 is added to the cumulative value. That is, the target of the cumulative value absDsum is from t12 to t36.

[0097] FIG. 7 shows the change in air pressure caused by the door opening and closing experiment, and FIG. 8 shows the processing of the erroneous in-bed determination caused by the air pressure change of a typhoon. For example, FIG. 7(a) and FIG. 8(a) are examples of operations when outputting as a sleep diary. The sleep diary in FIG. 7(a) is data in which the erroneous "in-bed" determination occurred due to the air pressure change caused by the door opening and closing experiment between about 10:11 and about 10:25 on November 19, and FIG. 8(a) is data in which the erroneous "in-bed" determination occurred due to the air pressure change of a typhoon between about 20:56 and about 21:40 on October 12. For each date, the upper row shows body movement, and the lower row shows the in-bed determination when the erroneous determination processing is not applied, with light colors representing awake (in bed) and dark colors representing asleep (in bed).

[0098] Figures 7(b) and 8(b) show vibration data representing the time when the conventional algorithm started to determine whether a patient was in bed due to a door opening / closing experiment and a false "in bed" determination caused by changes in air pressure due to a typhoon. Waveforms based on vibration data obtained from two sensors are shown above and below. Figure 7(b) shows vibration data mainly from the N100 portion of the sleep diary. Figure 8(b) shows vibration data mainly from the N110 portion of the sleep diary.

[0099] In FIG. 7(b), the color of the vibration data changes from light gray to black at approximately 10:11:08 (time t100), and this time t100 is the point at which the "in bed" erroneous determination started before the application of the erroneous determination processing unit of this embodiment. Since vibration is detected by the sensor of the detection device 3, the state in FIG. 7(b) is actually a state in which the subject is in bed. Similarly, in FIG. 8(b), the color of the vibration data changes from light gray to black at approximately 20:56:15 (time t110), and this time t110 is the point at which the "in bed" erroneous determination started before the application of this algorithm.

[0100] However, by applying the erroneous judgment process of this embodiment, the control unit 100 can judge that the subject has left the bed after time t100. For example, the bed leaving judgment is applied at approximately 10:11:08 (time t102) in Fig. 7(b) and at approximately 20:56:30 (time t112) in Fig. 8(b). That is, even though vibration data is being output, the control unit 100 can judge that the subject has left the bed.

[0101] Fig. 7(c) shows an example of parameter settings when applying processing. Here, the sampling rate at the time of file selection (e.g., 128Hz), whether to apply low-pass filter processing, and whether to apply data scale are set.

[0102] Also, it is possible to set a judgment time and a judgment coefficient for calculating a judgment value according to the number of bits. In FIG. 7(c), in the case of 12 bits, the judgment time (accumulated time) is 10 seconds and the judgment coefficient is 24. In the case of 10 bits, the judgment time (accumulated time) is 10 seconds and the judgment coefficient is 9. This means that if the vibration data of raw0 and raw1 are close to each other for 10 seconds, it is judged as getting out of bed. Note that these parameters are just an example and may also be applied to FIG. 8.

[0103] It is advisable to change the judgment coefficient according to the environment. For example, a judgment coefficient is set for each of the following: air pressure change due to opening and closing of doors and windows, air pressure change due to strong winds such as typhoons, air pressure change due to operation of air conditioners and ventilation fans, vibrations due to operation of electric beds, pressure changes of air mattresses, and other vibration-emitting devices, and vibrations due to engine operation of motorized automobiles and trains. The judgment coefficient is smallest for air pressure change, which is unlikely to cause a difference between the left and right sides of the sensor input, and large for air conditioners, vibrations due to contact with devices, engine operation, etc., which are likely to cause a difference between the left and right sides. Then, by switching the judgment coefficient according to the environment, appropriate bed exit and occupancy judgment can be performed.

[0104] For example, Fig. 9 is a diagram showing an example of a setting table for data in which vibration data has been quantized to 12 bits. The setting table is a table for setting the judgment coefficient D, and stores, for example, setting items and judgment coefficients in association with each other. For example, as setting items, a setting name (first setting), the environment of that setting (e.g., "air conditioner"), and a judgment coefficient D (e.g., "40") are stored.

[0105] For example, the coefficient may be set by staff or the like depending on the environment in which the sensor device is placed, or the control unit 100 may automatically acquire and set the environment. The control unit 100 may also automatically change the coefficient depending on the judgment result. For example, the control unit 100 may automatically reduce the judgment coefficient when the bed exit / occupancy judgment is not performed correctly because the judgment coefficient is large. For example, when the accuracy rate (match rate) between the specific timing of exit / occupancy input by the staff and the result judged by the control unit 100 is less than 80%, the control unit 100 may change the judgment coefficient D.

[0106] 9 may store a judgment value and a judgment time. That is, the setting table may store any of the parameters used by the control unit 100, such as a judgment coefficient, a judgment time, and a judgment value, for each setting item (for example, the location where the sensor is placed, the environment such as the weather and the presence or absence of an air conditioner, and the individual of the subject).

[0107] [5. Modifications] Although an embodiment of the present invention has been described in detail above with reference to the drawings, the specific configuration is not limited to this embodiment, and designs that do not deviate from the gist of the present invention are also included in the scope of the claims.

[0108] In addition, in this embodiment, the processing device 5 outputs the biological information based on the result output by the detection device 3, but all the calculations may be performed by the detection device 3. Also, instead of implementing it by installing an application on a terminal device (e.g., a smartphone, a tablet, or a computer), for example, the processing may be performed on the server side and the processing result may be returned to the terminal device.

[0109] For example, the above-mentioned process may be implemented on the server side by uploading vibration data from the detection device 3 to the server. The detection device 3 may be implemented as a device such as a smartphone having a built-in acceleration sensor and vibration sensor.

[0110] In addition, the programs that run on each device in the embodiments are programs that control the CPU and the like (programs that make a computer function) so as to realize the functions of the above-described embodiments. Information handled by these devices is temporarily stored in a temporary storage device (e.g., RAM) during processing, and is then stored in various types of ROM, HDD, and SSD storage devices, and is read, modified, and written by the CPU as necessary.

[0111] In addition, when distributing the program on the market, the program can be stored in a portable recording medium and distributed, or transferred to a server computer connected via a network such as the Internet. In this case, the storage device of the server computer is of course included in the present invention. [Explanation of symbols]

[0112] 1 System 3. Detection device 3 Processing equipment 100 Control section 102 Bed exit judgment unit 104 False positive processing unit 106 Biometric information calculation unit 108 Subject status determination unit 120 Signal Acquisition Unit 150 Storage section 152 Subject data storage area 154 Acquired data storage area 156 Parameter Table 160 Input section 170 Output section 10 Beds 20 Mattress

Claims

1. The bed device includes an acquisition unit that acquires vibration data from a first sensor installed in the bed device and a second sensor that is provided at a predetermined distance from the first sensor, and a control unit; The control unit is When the vibration data acquired from the first sensor and the vibration data acquired from the second sensor are substantially identical to each other, it is determined that the subject has left the bed; Calculating a difference between the vibration data acquired from the first sensor and the vibration data acquired from the second sensor; The difference in the vibration data is accumulated, and when the accumulated value is equal to or less than a predetermined judgment value and a judgment time has elapsed, the bed device judges that the subject has left the bed. A determination device characterized by:

2. A bed device comprising: an acquisition unit that acquires vibration data from a first sensor installed in the bed device and a second sensor installed at a predetermined distance from the first sensor; and a control unit; The control unit is When the vibration data acquired from the first sensor and the vibration data acquired from the second sensor are substantially identical to each other, it is determined that the subject has left the bed; When vibration is detected on the bed apparatus from the vibration data, it is determined that a subject is present in the bed apparatus; Even if it is determined that the subject is present on the bed device, the difference in the vibration data is accumulated, and if the accumulated value is equal to or less than a predetermined judgment value and a judgment time has elapsed, the bed device determines that the subject has left the bed. A determination device characterized by:

3. A bed device comprising: an acquisition unit that acquires vibration data from a first sensor installed in the bed device and a second sensor that is provided at a predetermined distance from the first sensor; and a control unit; The control unit is When the vibration data acquired from the first sensor and the vibration data acquired from the second sensor are substantially identical to each other, it is determined that the subject has left the bed; Calculating a difference between the vibration data acquired from the first sensor and the vibration data acquired from the second sensor; When a difference equal to or smaller than a predetermined judgment value is continuously detected for a predetermined period of time, the bed device judges that the subject has left the bed. A determination device characterized by:

4. A bed device comprising: an acquisition unit that acquires vibration data from a first sensor installed in the bed device and a second sensor installed at a predetermined distance from the first sensor; and a control unit; The control unit is When the vibration data acquired from the first sensor and the vibration data acquired from the second sensor are substantially identical to each other, it is determined that the subject has left the bed; Calculating a correlation coefficient between the vibration data acquired from the first sensor and the vibration data acquired from the second sensor; When the correlation coefficient is equal to or greater than a predetermined judgment value, the bed device judges that the subject has left the bed. A determination device characterized by:

5. The control unit is The subject's sleep or wakefulness can be determined from the vibration data, When the sleep or wakefulness of the subject is not determined, the subject is determined to have left the bed.

5. The determination device according to claim 1, wherein the determination device further comprises:

6. The bed device includes an acquisition unit that acquires vibration data from a first sensor installed in the bed device and a second sensor that is provided at a predetermined distance from the first sensor, and a control unit; The control unit is When the vibration data acquired from the first sensor and the vibration data acquired from the second sensor are substantially identical to each other, it is determined that the subject has left the bed; When the vibration data acquired from the first sensor or the vibration data acquired from the second sensor is greater than a predetermined value, a process of attenuating the vibration data greater than the predetermined value is executed; When the vibration data is not attenuated, it is determined that the subject has left the bed. A determination device characterized by:

7. 5. The determination device according to claim 1, wherein the determination value corresponds to a change in atmospheric pressure.

8. A determination device described in any one of claims 1 to 6, wherein the second sensor is arranged at a distance from the first sensor that is the lateral width of the patient.

9. A determination device described in any one of claims 1 to 6, wherein the distance between the first sensor and the second sensor is 15 to 60 cm.

10. A determination device as described in claim 8 or 9, wherein the first sensor and the second sensor are placed in a position near the back of a patient using the bed device.

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